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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 815 · 40 questions
TalentJR

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

NameDateTime takenScore ___ / 40
  1. 1.True or false: turning spoken words into typed text only needs a simple fixed rule. (a) True (b) False
  2. 2.True or false: “examples of every type” is bad for training a model. (a) True (b) False
  3. 3.🔁 Training data, the model or a prediction: “labelled fruit photos”? (a) a prediction (b) training data (c) the model
  4. 4.Which of these uses AI? (a) a digital watch (b) a printed timetable (c) a spam filter (d) a torch
  5. 5.🎨 This prompt asks a generative AI for: write a poem about the monsoon. What kind of output is that? (a) music or sound (b) text (c) an image
  6. 6.True or false: a camera app naming the flower you point at is AI recognising something. (a) True (b) False
  7. 7.📚 Good or bad for training a model: clear, sharp examples? (a) bad for training (b) good for training
  8. 8.🔍 Which is the odd one out? (a) long answers are true (b) AI answers need checking (c) AI learns from data (d) AI can be wrong
  9. 9.Which of these is generative AI (it makes something new)? (a) unlocking with a face (b) sorting photos by face (c) suggesting a video (d) writing quiz questions
  10. 10.💬 What do we call the request you type to a generative AI? (a) a password (b) a battery (c) a prompt (d) a label
  11. 11.True or false: “500 labelled leaf photos” is a prediction. (a) False (b) True
  12. 12.True or false: the message “Happy birthday! See you at lunch” should be labelled “not spam”. (a) False (b) True
  13. 13.🛠️ Does this reduce bias or add to it: fix wrong labels? (a) reduces bias (b) adds to bias
  14. 14.🔁 Training data, the model or a prediction: “flagging a new email”? (a) training data (b) a prediction (c) the model
  15. 15.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) predicting (c) drawing (d) sleeping
  16. 16.🤖 AI or a normal program: which one “uses rules people wrote”? (a) a normal program (b) AI
  17. 17.🔦 Is a torch with an on/off switch AI? (a) yes (b) only if it is bright (c) no
  18. 18.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will turn yellow (b) it will shut down (c) it will be perfect (d) it may get it wrong
  19. 19.📚 Usually, more good examples make a model… (a) change colour (b) better at its task (c) slower to switch on (d) forget everything
  20. 20.True or false: the message “Earn ₹50,000 a day from home!!!” should be labelled “not spam”. (a) True (b) False
  21. 21.True or false: “what training builds” is training data. (a) True (b) False
  22. 22.📚 Good or bad for training a model: very few examples? (a) bad for training (b) good for training
  23. 23.🔍 Which is the odd one out? (a) making up a story (b) drafting a letter (c) turning speech to text (d) inventing a recipe
  24. 24.✅ Is this a real check of an AI answer: it sounds very sure? (a) a real check (b) not a real check
  25. 25.✅ Is this a real check of an AI answer: it has a neat layout? (a) a real check (b) not a real check
  26. 26.📦 What happens during training? (a) it takes photos (b) it charges up (c) it learns patterns (d) it prints labels
  27. 27.🔍 Which is the odd one out? (a) AI knows everything (b) AI always checks facts (c) AI has real feelings (d) AI can be wrong
  28. 28.🔁 Training data, the model or a prediction: “what training builds”? (a) a prediction (b) the model (c) training data
  29. 29.True or false: “what training builds” is the model. (a) True (b) False
  30. 30.✅ Is this a real check of an AI answer: match it to the textbook? (a) not a real check (b) a real check
  31. 31.🔍 Which is the odd one out? (a) a printed timetable (b) a microwave timer (c) a torch (d) a spam filter
  32. 32.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
  33. 33.✨ Is everything a generative AI makes true? (a) yes, always (b) no, it can be wrong (c) only on Mondays
  34. 34.🔍 Which is the odd one out? (a) ask different people (b) add varied examples (c) balance the data (d) add more of the same
  35. 35.🤖 Who builds and trains AI systems? (a) the weather (b) the Moon (c) people (d) nobody at all
  36. 36.📚 Good or bad for training a model: correct labels? (a) good for training (b) bad for training
  37. 37.True or false: leaves from every season of the year is one-sided data (likely to make a biased model). (a) True (b) False
  38. 38.Which of these describes how AI works? (a) same steps every time (b) follows fixed rules (c) never learns from data (d) spots patterns in data
  39. 39.Which of these is bad for training a model? (a) new data for testing (b) photos in many lights (c) very few examples (d) many varied examples
  40. 40.🏠 AI or not AI: a doorbell? (a) not AI (b) uses AI

Answer key

  1. False
  2. False
  3. training data
  4. a spam filter
  5. text
  6. True
  7. good for training
  8. long answers are true
  9. writing quiz questions
  10. a prompt
  11. False
  12. True
  13. reduces bias
  14. a prediction
  15. predicting
  16. a normal program
  17. no
  18. it may get it wrong
  19. better at its task
  20. False
  21. False
  22. bad for training
  23. turning speech to text
  24. not a real check
  25. not a real check
  26. it learns patterns
  27. AI can be wrong
  28. the model
  29. True
  30. a real check
  31. a spam filter
  32. False
  33. no, it can be wrong
  34. add more of the same
  35. people
  36. good for training
  37. False
  38. spots patterns in data
  39. very few examples
  40. not AI

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